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Record W2781711192 · doi:10.1152/ajpheart.00339.2017

Guidelines for measuring cardiac physiology in mice

2018· article· en· W2781711192 on OpenAlexafffund
Merry L. Lindsey, Zamaneh Kassiri, Jitka A. I. Virag, Lisandra E. de Castro Brás, Marielle Scherrer‐Crosbie

Bibliographic record

VenueAmerican Journal of Physiology-Heart and Circulatory Physiology · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsUniversity of Alberta
FundersHeart and Stroke Foundation of CanadaNational Heart, Lung, and Blood InstituteNational Institutes of HealthNational Institute of General Medical SciencesAmerican Heart AssociationU.S. Department of Veterans Affairs
KeywordsCardiovascular physiologyDiseaseMedicineTranslational researchPhysiologyNeuroscienceBioinformaticsIntensive care medicinePathologyCardiologyBiology

Abstract

fetched live from OpenAlex

Cardiovascular disease is a leading cause of death, and translational research is needed to understand better mechanisms whereby the left ventricle responds to injury. Mouse models of heart disease have provided valuable insights into mechanisms that occur during cardiac aging and in response to a variety of pathologies. The assessment of cardiovascular physiological responses to injury or insult is an important and necessary component of this research. With increasing consideration for rigor and reproducibility, the goal of this guidelines review is to provide best-practice information regarding how to measure accurately cardiac physiology in animal models. In this article, we define guidelines for the measurement of cardiac physiology in mice, as the most commonly used animal model in cardiovascular research. Listen to this article's corresponding podcast at http://ajpheart.podbean.com/e/guidelines-for-measuring-cardiac-physiology-in-mice/ .

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.022
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.022
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.026
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0060.002
Science and technology studies0.0020.002
Scholarly communication0.0030.002
Open science0.0070.002
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0220.026

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.299
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations332
Published2018
Admission routes2
Has abstractyes

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Same venueAmerican Journal of Physiology-Heart and Circulatory PhysiologySame topicCardiac electrophysiology and arrhythmiasFrench-language works237,207